Minor typofixes

tutorial/paper/paper.md

@@ -79,7 +79,7 @@ Traditionally, the dynamics of compact binary systems and the emitted gravitatio
 
 ![Example gravitational wave prediction from a surrogate model compared with numerical relativity for a precessing binary black hole system. This particular numerical relativity simulation took 70,881 CPU-hours (about 1.75 months using 56 cores on the supercomputer Frontera), while the surrogate model can be evaluated in about 100 milliseconds. \label{fig:gws}](gwsurrogate.png)
 
-Surrogate models offer a practical way to dramatically accelerate model evaluation while retaining the high-fidelity accuracy of the expensive simulation code; an example is shown in Fig.\ref{fig:gws}. Surrogate models can be constructed in various ways, but what separates these models from other modeling frameworks is that they are primarily data-driven. Given a training set of gravitational waveform data sampling the parameter space, a model is built by following three steps:
+Surrogate models offer a practical way to dramatically accelerate model evaluation while retaining the high-fidelity accuracy of the expensive simulation code; an example is shown in Fig. \ref{fig:gws}. Surrogate models can be constructed in various ways, but what separates these models from other modeling frameworks is that they are primarily data-driven. Given a training set of gravitational waveform data sampling the parameter space, a model is built by following three steps:
 
 1. Feature extraction: the waveform is decomposed into *data pieces* that are simple to model,
 2. Dimensionality reduction: each data piece is approximated by a low-dimensional vector space, which reduces the degrees of freedom we need to model, and 
@@ -102,11 +102,11 @@ where $^{-2}Y_{\ell m}$ are the spin$=-2$ weighted spherical harmonics and $\Lam
 - models implemented in ``GWSurrogate`` follow the waveform convention choices of the LIGO-Virgo-Kagra collaboration, thus ensuring that downstream data analysis codes can use ``GWSurrogate`` models without needing to worry about different conventions, and
 - ``GWSurrogate`` models can be directly evaluated in either physical units (often used in data analysis studies) and dimensionless units (often used in theoretical studies) where all dimensioned quantities are expressed in terms of the system's total mass.
 
-Currently, there are 15 supported surrogate models (@Blackman:2015pia, @OShaughnessy:2017tak, @Blackman:2017dfb, @Varma:2018mmi, @Yoo:2023spi, @Yoo:2022erv, @Varma:2019csw, @Barkett:2019tus, @Rifat:2019ltp, @Islam:2022laz, @Field:2013cfa). These models vary in their duration, included physical effects (e.g. nonlinear memory, tidal forces, harmonic modes retained, eccentricity, mass ratio extent, precession effects, etc), and underlying solution method (e.g. Effective One Body, numerical relativity, and black hole perturbation theory). Details about all models can be found by doing `gws.catalog.list(verbose=True)`, while the ``GWSurrogate`` [homepage](https://github.com/sxs-collaboration/gwsurrogate) summarizes the state-of-the-art models for each particular problem. Certain models allow for additional functionality such as returning the dynamics of the binary black hole; these special features are described further in model-specific [example notebooks](https://github.com/sxs-collaboration/gwsurrogate/tree/master/tutorial).
+Currently, there are 15 supported surrogate models (@Blackman:2015pia, @OShaughnessy:2017tak, @Blackman:2017dfb, @Varma:2018mmi, @Yoo:2023spi, @Yoo:2022erv, @Varma:2019csw, @Barkett:2019tus, @Rifat:2019ltp, @Islam:2022laz, @Field:2013cfa). These models vary in their duration, included physical effects (e.g. nonlinear memory, tidal forces, harmonic modes retained, eccentricity, mass ratio extent, precession effects, etc), and underlying solution method (e.g. Effective One Body, numerical relativity, and black hole perturbation theory). Details about all models can be found by doing `gwsurrogate.catalog.list(verbose=True)`, while the ``GWSurrogate`` [homepage](https://github.com/sxs-collaboration/gwsurrogate) summarizes the state-of-the-art models for each particular problem. Certain models allow for additional functionality such as returning the dynamics of the binary black hole; these special features are described further in model-specific [example notebooks](https://github.com/sxs-collaboration/gwsurrogate/tree/master/tutorial).
 
 
 # Acknowledgements
 
 We acknowledge our many close collaborators for their contribution to the development of surrogate models. We further acknowledge the community of ``GWSurrogate`` users who have contributed pull requests and opened issues, including Kevin Barkett, Mike Boyle, Collin Capano, Dwyer Deighan, Raffi Enficiaud, Oliver Jennrich, Duncan Macleod, Alex Nitz, Seth Olsen, Swati Singh, and Avi Vajpeyi. ``GWSurrogate`` has been developed over the past 10 years with continued support from the National Science Foundation, most recently through NSF grants PHY-2110496, PHY-2309301, and DMS-2309609.
 
-# References
+# References